Title :
Image denoising based on the one-dimensional LPA-RICI method
Author :
Lerga, Jonatan ; Sucic, Victor ; Sersic, Damir
Author_Institution :
Fac. of Eng., Univ. of Rijeka, Rijeka, Croatia
Abstract :
The recently proposed signal denoising method based on the relative intersection of confidence intervals (RICI) rule combined with local polynomial approximation is applied to image denoising, with images being transformed to one-dimensional signals. The obtained results, in the terms of peak signal-to-noise ratio (PSNR), are compared to the results obtained using the approach based on the intersection of confidence (ICI) rule. It is shown that the denoising approach using the LPA-RICI method outperforms the one using the LPA-ICI method. Although the proposed denoising approach does not outperform the state-of-the-art denoising techniques, the main advantages of the one-dimensional image denoising algorithm are its simplicity, and the fact that it is computationally less demanding than two-dimensional anisotropic image denoising approaches.
Keywords :
image denoising; polynomial approximation; intersection of confidence rule; local polynomial approximation; one-dimensional LPA-RICI method; one-dimensional image denoising algorithm; peak signal-to-noise ratio; relative intersection of confidence intervals rule; signal denoising method; state of the art denoising techniques; two-dimensional anisotropic image denoising; Adaptive filters; Additive noise; Digital images; Filtering algorithms; Image denoising; Noise reduction; PSNR; Polynomials; Signal processing algorithms; Wavelet coefficients; Image denoising; adaptive filtering; adaptive varying window selection; image restoration; intersection of confidence intervals (ICI) rule; local polynomial approximation (LPA); one-dimensional signal processing; relative intersection of confidence intervals (RICI) rule;
Conference_Titel :
ELMAR, 2009. ELMAR '09. International Symposium
Conference_Location :
Zadar
Print_ISBN :
978-953-7044-10-7